Tackling climate change with machine learning
Climate change is one of the greatest challenges facing humanity, and we, as machine
learning (ML) experts, may wonder how we can help. Here we describe how ML can be a …
learning (ML) experts, may wonder how we can help. Here we describe how ML can be a …
Deep learning (CNN, RNN) applications for smart homes: a systematic review
J Yu, A de Antonio, E Villalba-Mora - Computers, 2022 - mdpi.com
In recent years, research on convolutional neural networks (CNN) and recurrent neural
networks (RNN) in deep learning has been actively conducted. In order to provide more …
networks (RNN) in deep learning has been actively conducted. In order to provide more …
[HTML][HTML] Progress and framework of clean energy production: Bibliometric analysis from 2002 to 2022
Y Geng, Q Xiang, J Gao, Y Yan, J Li - Energy Strategy Reviews, 2024 - Elsevier
Current society prioritizes clean energy production (CEP) to meet diverse energy needs and
achieve sustainability. Current research involves different aspects of CEP, but …
achieve sustainability. Current research involves different aspects of CEP, but …
LSTM-based indoor air temperature prediction framework for HVAC systems in smart buildings
Accurate indoor air temperature (IAT) predictions for heating, ventilation, and air
conditioning (HVAC) systems are challenging, especially for multi-zone building and for …
conditioning (HVAC) systems are challenging, especially for multi-zone building and for …
Day ahead carbon emission forecasting of the regional National Electricity Market using machine learning methods
V Aryai, M Goldsworthy - Engineering Applications of Artificial Intelligence, 2023 - Elsevier
Accurate forecasting of regional electrical grid carbon emissions is an essential part of
demand response programs for emissions reduction. Most existing research for short-term …
demand response programs for emissions reduction. Most existing research for short-term …
Deep learning-based resource allocation for 5G broadband TV service
The vision of next-generation TV is to support media services to achieve sharing of cross-
domain experience, and the eMBB scenario of the 5G network is one of its important driving …
domain experience, and the eMBB scenario of the 5G network is one of its important driving …
How well do emission factors approximate emission changes from electricity system models?
Multiple forms of marginal and average emission factors have been developed to estimate
the carbon emissions of adding technologies, such as electric vehicles or solar panels, to …
the carbon emissions of adding technologies, such as electric vehicles or solar panels, to …
Emerging Sociotechnical Imaginaries–How the smart home is legitimized in visions from industry, users in homes and policymakers in Germany
F Rohde, T Santarius - Futures, 2023 - Elsevier
Debates about the digitally enhanced and “smart” home include different visions associated
with implementing digital technologies in private homes. This paper analyzes the “visions” …
with implementing digital technologies in private homes. This paper analyzes the “visions” …
Impacts of collaborative partnership on the performance of cold supply chains of agriculture and foods: literature review
Collaboration in a supply chain continuously proves its role in increasing the performance of
supply chains, which attracts the attention of both academia and practitioners, specifically …
supply chains, which attracts the attention of both academia and practitioners, specifically …
[HTML][HTML] Deakin microgrid digital twin and analysis of AI models for power generation prediction
To achieve carbon neutral by 2025, Deakin University launched a AUD 23 million
Renewable Energy Microgrid in 2020 with a 7-megawatt solar farm, the largest at an …
Renewable Energy Microgrid in 2020 with a 7-megawatt solar farm, the largest at an …